Adaptive Sensor Fusion for Automotive Emergency Braking in Adverse Weather
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing automotive braking control systems fail to accurately determine the possibility of a collision with a forward object in adverse weather conditions such as rainfall, heavy snowfall, or fog, leading to increased braking distances and potential collisions due to reduced friction coefficients and inaccurate camera image information.
Innovation Solution
An automotive braking control system that includes a camera module for image data processing, a non-image sensor module for sensing data processing, and a control unit that determines weather conditions and adjusts the weight of image and sensing information to accurately assess collision possibilities, thereby controlling emergency braking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the system uses camera image information to determine collision possibility, then object recognition is achieved, but measurement precision deteriorates in adverse weather conditions such as rainfall, heavy snowfall, or fog
Solution Approach 1:
The patent introduces radar as an intermediary sensing device that operates effectively in adverse weather conditions where camera-based optical sensing fails. The radar serves as a mediator to detect forward objects when atmospheric conditions (rain, snow, fog) degrade camera performance, ensuring continuous and reliable object recognition across all weather scenarios
Solution Approach 2:
The system dynamically changes the weighting parameters of different sensing devices based on detected weather conditions. When adverse weather is detected, the system increases the weight of radar information and decreases the weight of camera image information in the fusion algorithm, optimizing measurement precision by adapting to environmental parameter changes
2Reliability
If the system performs emergency braking based on collision possibility determination, then collision avoidance is achieved, but braking distance increases in adverse weather conditions due to reduced friction coefficient
Solution Approach 1:
The system performs preliminary detection and assessment of adverse weather conditions and potential collision risks before initiating emergency braking. By identifying weather-related friction reduction in advance and calculating adjusted safe stopping distances, the system can trigger earlier braking commands or adjust braking intensity to compensate for reduced road surface friction, thereby maintaining collision avoidance reliability despite increased braking distances
Solution Approach 2:
The system continuously monitors weather conditions and adjusts braking control parameters based on real-time feedback about road surface friction characteristics. When adverse weather is detected, the feedback loop modifies braking force application and timing to account for reduced friction coefficients, ensuring reliable collision avoidance while optimizing braking performance under varying environmental conditions
3Device complexity
If the system equally weights image information and object sensing information from radar, then processing simplicity is maintained, but measurement precision deteriorates in adverse weather conditions
Solution Approach 1:
The patent transforms the static, fixed-weight fusion algorithm into a dynamic system that automatically adjusts the weighting of camera and radar information based on real-time weather condition assessment. The system remains relatively simple in structure but gains adaptive capability through dynamic parameter adjustment, maintaining measurement precision across varying environmental conditions without requiring complex manual reconfiguration
Solution Approach 2:
The system changes the weighting parameters of sensor fusion based on detected weather conditions. In clear weather, equal weighting maintains simplicity. In adverse weather, the system automatically adjusts parameters to increase radar weight and decrease camera weight, improving measurement precision while adding only minimal computational complexity through conditional parameter adjustment
Data Source
AI summary
The present disclosure relates to an automotive braking control apparatus and method. The automotive braking control apparatus includes: a weather condition determiner determining weather conditions on the basis of image information received from a camera; a collision determiner determining possibility of a collision with a forward object on the basis of the image information received from the camera and object sensing information received from a radar; and an automotive braking controller controlling emergency braking of a vehicle when it is determined that there is possibility of a collision with the forward object, in which the collision determiner changes weight for the image information and weight for the object sensing information on the basis of the weather conditions.